Intro to AI for GLAM

This lesson aims to empower GLAM (Galleries, Libraries, Archives, and Museums) staff by providing the foundation to support, participate in and begin to undertake in their own right, machine learning-based research and projects with heritage collections.

After attending, learners will be able to:

Explain and differentiate key terms, phrases, and concepts associated with AI and Machine Learning in GLAM
Describe ways in which AI is being innovatively used in the cultural heritage context today
Identify what kinds of tasks machine learning models excel at in GLAM applications
Identify weaknesses in machine learning models
Reflect on ethical implications of applying machine learning to cultural heritage collections and discuss potential mitigation strategies
Summarise the practical, technical steps involved in undertaking machine learning projects
Identify additional resources on AI and Machine Learning in GLAM

Prerequisites

None

Schedule

	Setup	Download files required for the lesson
00:00	1. Welcome	Who is this lesson for? What will we be covering in this lesson? What will we not be covering in this lesson?
00:05	2. Artificial Intelligence (AI) and Machine Learning (ML) in a nutshell	What is a brief history of the field of (AI) and Machine Learning (ML)? What do we mean by Artificial Intelligence and Machine Learning? How are they defined?
00:05	3. Machine Learning Modelling Concepts	What are models and algorithms? What factors should we consider when choosing a machine learning model?
00:05	4. What is Machine Learning good at?	What are the tasks where machine learning excels?
00:45	5. Understanding and managing bias	What are common types of bias and their effect in machine learning? At what points can bias enter the machine learning pipeline? Can we manage bias? Some lessons from GLAM
00:45	6. Applying Machine Learning	What are the key steps involved in a machine learning project? What skills and people should be involved in a machine learning project? How can machine learning models predictions be utilised by an organization?
00:45	7. The Machine Learning ecosystem	FIXME
00:45	Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.